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2http://www.cs.wisc.edu/condor
The Condor Project (Established ‘85)
Distributed High Throughput Computing research performed by a team of ~35 faculty, full time staff and students.
3http://www.cs.wisc.edu/condor
Definitions› Job
The Condor representation of your work
› Machine The Condor representation of
computers and that can perform the work
› Match Making Matching a job with a machine
“Resource”
4http://www.cs.wisc.edu/condor
Job
Jobs state their requirements and preferences:I need a Linux/x86 platformI need the machine at least 500 MbI prefer a machine with more memory
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Machine
Machines state their requirements and preferences:Run jobs only when there is no keyboard
activityI prefer to run Frieda’s jobsI am a machine in the econ departmentNever run jobs belonging to Dr. Smith
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The Magic of Matchmaking
› Jobs and machines state their requirements and preferences
› Condor matches jobs with machinesbased on requirements and
preferences
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Getting Started:Submitting Jobs to
Condor› Overview:
Choose a “Universe” for your job Make your job “batch-ready” Create a submit description file Run condor_submit to put your job in
the queue
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1. Choose the “Universe”› Controls how Condor handles jobs
› Choices include: Vanilla Standard Grid Java Parallel VM
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Using the Vanilla Universe
• The Vanilla Universe:– Allows running
almost any “serial” job
– Provides automatic file transfer, etc.
– Like vanilla ice cream• Can be used in just
about any situation
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2. Make your job batch-ready
Must be able to run in the background
• No interactive input
• No GUI/window clicks
• No music ;^)
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Make your job batch-ready (continued)…
Job can still use STDIN, STDOUT, and STDERR (the keyboard and the screen), but files are used for these instead of the actual devices
Similar to UNIX shell:•$ ./myprogram <input.txt >output.txt
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3. Create a Submit Description File
› A plain ASCII text file
› Condor does not care about file extensions
› Tells Condor about your job: Which executable, universe, input, output and
error files to use, command-line arguments, environment variables, any special requirements or preferences (more on this later)
› Can describe many jobs at once (a “cluster”), each with different input, arguments, output, etc.
13http://www.cs.wisc.edu/condor
Simple Submit Description File
# Simple condor_submit input file# (Lines beginning with # are comments)# NOTE: the words on the left side are not# case sensitive, but filenames are!Universe = vanillaExecutable = my_jobOutput = output.txt Queue
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4. Run condor_submit› You give condor_submit the name
of the submit file you have created: condor_submit my_job.submit
› condor_submit: Parses the submit file, checks for
errors Creates a “ClassAd” that describes
your job(s) Puts job(s) in the Job Queue
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The Job Queue
› condor_submit sends your job’s ClassAd(s) to the schedd
› The schedd (more details later): Manages the local job queue Stores the job in the job queue
• Atomic operation, two-phase commit• “Like money in the bank”
› View the queue with condor_q
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Examplecondor_submit and
condor_q% condor_submit my_job.submitSubmitting job(s).1 job(s) submitted to cluster 1.
% condor_q
-- Submitter: perdita.cs.wisc.edu : <128.105.165.34:1027> : ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD
1.0 frieda 6/16 06:52 0+00:00:00 I 0 0.0 my_job
1 jobs; 1 idle, 0 running, 0 held
%
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Input, output & error files› Controlled by submit file settings
› You can define the job’s standard input, standard output and standard error: Read job’s standard input from “input_file”:
• Input = input_file• Shell equivalent: program <input_file
Write job’s standard ouput to “output_file”:• Output = output_file• Shell equivalent: program >output_file
Write job’s standard error to “error_file”:• Error = error_file• Shell equivalent: program 2>error_file
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Email about your job
• Condor sends email about job events to the submitting user
• Specify “notification” in your submit file to control which events:
Notification = completeNotification = neverNotification = errorNotification = always
Default
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Feedback on your job
› Create a log of job events
› Add to submit description file:log = sim.log
› Becomes the Life Story of a Job Shows all events in the life of a job Always have a log file
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Sample Condor User Log
000 (0001.000.000) 05/25 19:10:03 Job submitted from host: <128.105.146.14:1816>
...
001 (0001.000.000) 05/25 19:12:17 Job executing on host: <128.105.146.14:1026>
...
005 (0001.000.000) 05/25 19:13:06 Job terminated.
(1) Normal termination (return value 0)
...
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Example Submit Description File With
Logging# Example condor_submit input file# (Lines beginning with # are comments)# NOTE: the words on the left side are not# case sensitive, but filenames are!Universe = vanillaExecutable = /home/frieda/condor/my_job.condorLog = my_job.log ·Job log (from Condor)Input = my_job.in ·Program’s standard inputOutput = my_job.out ·Program’s standard outputError = my_job.err ·Program’s standard errorArguments = -a1 -a2 ·Command line argumentsInitialDir = /home/frieda/condor/runQueue
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Let’s run a job
› First, need a terminal emulator http://www.putty.org
• (or similar)
› Login to chopin.cs.wisc.edu as cguserXX, and the given password
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Create submit file
› nano submit.your_initials• universe = vanilla• executable = /bin/echo• Arguments = hello world• Output = out• Log = log• queue
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And submit it…
› condor_submit submit.your_initials
› (wait… remember the HTC bit?)
› Condor_q xx
› cat output
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“Clusters” and “Processes”
› If your submit file describes multiple jobs, we call this a “cluster”
› Each cluster has a unique “cluster number”› Each job in a cluster is called a “process”
Process numbers always start at zero› A Condor “Job ID” is the cluster number, a period,
and the process number (i.e. 2.1) A cluster can have a single process
• Job ID = 20.0 ·Cluster 20, process 0 Or, a cluster can have more than one process
• Job ID: 21.0, 21.1, 21.2 ·Cluster 21, process 0, 1, 2
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Submit File for a Cluster# Example submit file for a cluster of 2 jobs
# with separate input, output, error and log filesUniverse = vanillaExecutable = my_jobArguments = -x 0log = my_job_0.logInput = my_job_0.inOutput = my_job_0.outError = my_job_0.errQueue ·Job 2.0 (cluster 2, process 0)Arguments = -x 1log = my_job_1.logInput = my_job_1.inOutput = my_job_1.outError = my_job_1.errQueue ·Job 2.1 (cluster 2, process 1)
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% condor_submit my_job.submit-file
Submitting job(s).
2 job(s) submitted to cluster 2.
% condor_q
-- Submitter: perdita.cs.wisc.edu : <128.105.165.34:1027> :
ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD
1.0 frieda 4/15 06:52 0+00:02:11 R 0 0.0 my_job –a1 –a2
2.0 frieda 4/15 06:56 0+00:00:00 I 0 0.0 my_job –x 0
2.1 frieda 4/15 06:56 0+00:00:00 I 0 0.0 my_job –x 1
3 jobs; 2 idle, 1 running, 0 held
%
Submitting The Job
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Organize your files and directories for big runs
› Create subdirectories for each “run” run_0, run_1, … run_599
› Create input files in each of these run_0/simulation.in run_1/simulation.in … run_599/simulation.in
› The output, error & log files for each job will be created by Condor from your job’s output
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Submit Description File for 600 Jobs
# Cluster of 600 jobs with different directoriesUniverse = vanillaExecutable = simLog = simulation.log...Arguments = -x 0
InitialDir = run_0 ·Log, input, output & error files -> run_0
Queue ·Job 3.0 (Cluster 3, Process 0)
Arguments = -x 1
InitialDir = run_1 ·Log, input, output & error files -> run_1
Queue ·Job 3.1 (Cluster 3, Process 1)
·Do this 598 more times…………
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Submit File for a Big Cluster of Jobs
› We just submitted 1 cluster with 600 processes
› All the input/output files will be in different directories
› The submit file is pretty unwieldy (over 1200 lines)
› Isn’t there a better way?
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Submit File for a Big Cluster of Jobs (the better
way) #1› We can queue all 600 in 1 “Queue” command Queue 600
› Condor provides $(Process) and $(Cluster) $(Process) will be expanded to the
process number for each job in the cluster• 0, 1, … 599
$(Cluster) will be expanded to the cluster number• Will be 4 for all jobs in this cluster
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Submit File for a Big Cluster of Jobs (the better
way) #2› The initial directory for each job can
be specified using $(Process) InitialDir = run_$(Process) Condor will expand these to “run_0”,
“run_1”, … “run_599” directories
› Similarly, arguments can be variable Arguments = -x $(Process) Condor will expand these to “-x 0”, “-x 1”, … “-x 599”
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Better Submit File for 600 Jobs
# Example condor_submit input file that defines# a cluster of 600 jobs with different directoriesUniverse = vanillaExecutable = my_jobLog = my_job.logInput = my_job.inOutput = my_job.outError = my_job.errArguments = –x $(Process) ·–x 0, -x 1, … -x
599InitialDir = run_$(Process) ·run_0 … run_599Queue 600 ·Jobs
4.0 … 4.599
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Now, we submit it…$ condor_submit my_job.submitSubmitting
job(s) ...............................................................................................................................................................................................................................................................
Logging submit event(s) ...............................................................................................................................................................................................................................................................
600 job(s) submitted to cluster 4.
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And, Check the queue$ condor_q
-- Submitter: x.cs.wisc.edu : <128.105.121.53:510> : x.cs.wisc.edu
ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD
4.0 frieda 4/20 12:08 0+00:00:05 R 0 9.8 my_job -arg1 –x 0
4.1 frieda 4/20 12:08 0+00:00:03 I 0 9.8 my_job -arg1 –x 1
4.2 frieda 4/20 12:08 0+00:00:01 I 0 9.8 my_job -arg1 –x 2
4.3 frieda 4/20 12:08 0+00:00:00 I 0 9.8 my_job -arg1 –x 3
...
4.598 frieda 4/20 12:08 0+00:00:00 I 0 9.8 my_job -arg1 –x 598
4.599 frieda 4/20 12:08 0+00:00:00 I 0 9.8 my_job -arg1 –x 599
600 jobs; 599 idle, 1 running, 0 held
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Removing jobs› If you want to remove a job from
the Condor queue, you use condor_rm
› You can only remove jobs that you own
› Privileged user can remove any jobs “root” on UNIX “administrator” on Windows
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Removing jobs (continued)
› Remove an entire cluster: condor_rm 4 ·Removes the whole
cluster
› Remove a specific job from a cluster: condor_rm 4.0 ·Removes a single job
› Or, remove all of your jobs with “-a” condor_rm -a ·Removes all jobs /
clusters
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Submit cluster of 10 jobs
› nano submit• universe = vanilla• executable = /bin/echo• Arguments = hello world $(PROCESS)• Output = out.$(PROCESS)• Log = log• Queue 10
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And submit it…
› condor_submit submit
› (wait…)
› Condor_q xx
› cat log
› cat output.yy
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My new jobs run for 20 days…
› What happens when a job is forced off it’s CPU? Preempted by higher priority
user or job Vacated because of user
activity
› How can I add fault tolerance to my jobs?
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Condor’s Standard Universe to the rescue!› Support for transparent process
checkpoint and restart› Remote system calls (remote
I/O)Your job can read / write files as if they were local
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Remote System Calls inthe Standard Universe
› I/O system calls are trapped and sent back to the submit machineExamples: open a file, write to a file
› No source code changes typically required
› Programming language independent
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Process Checkpointing in the
Standard Universe› Condor’s process checkpointing provides a mechanism to automatically save the state of a job
› The process can then be restarted from right where it was checkpointed After preemption, crash, etc.
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Checkpointing:Process Starts
checkpoint: the entire state of a program, saved in a file CPU registers, memory image, I/O
time
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When will Condor checkpoint your job?
› Periodically, if desired For fault tolerance
› When your job is preempted by a higher priority job
› When your job is vacated because the execution machine becomes busy
› When you explicitly run condor_checkpoint, condor_vacate, condor_off or condor_restart command
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Making the Standard Universe Work
› The job must be relinked with Condor’s standard universe support library
› To relink, place condor_compile in front of the command used to link the job:
% condor_compile gcc -o myjob myjob.c
- OR -
% condor_compile f77 -o myjob filea.f fileb.f
- OR -
% condor_compile make –f MyMakefile
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Limitations of the Standard Universe
› Condor’s checkpointing is not at the kernel level. Standard Universe the job may not:
• Fork()• Use kernel threads• Use some forms of IPC, such as pipes and shared
memory
› Must have access to source code to relink
› Many typical scientific jobs are OK
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Submitting Std uni job
› #include <stdio.h>
› int main(int argc, char **argv) {
› int i;for(i = 0 ; i < 10000000; i++) {}
› }
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And submit…
› condor_compile gcc –o foo foo.c
-- Change "vanilla" to "standard" -- Change "/bin/echo" to "foo" (or
above)
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My jobs have have dependencies…
Can Condor help solve my dependency problems?
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Condor Universes:Scheduler and Local
› Scheduler Universe Plug in a meta-scheduler Developed for DAGMan (more later) Similar to Globus’s fork job manager
› Local Very similar to vanilla, but jobs run on
the local host Has more control over jobs than
scheduler universe
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DAGMan
› Directed Acyclic Graph Manager
› DAGMan allows you to specify the dependencies between your Condor jobs, so it can manage them automatically for you.
› (e.g., “Don’t run job “B” until job “A” has completed successfully.”)
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What is a DAG?
› A DAG is the data structure used by DAGMan to represent these dependencies.
› Each job is a “node” in the DAG.
› Each node can have any number of “parent” or “children” nodes – as long as there are no loops!
Job A
Job B
Job C
Job D
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Defining a DAG
› A DAG is defined by a .dag file, listing each of its nodes and their dependencies:# diamond.dagJob A a.subJob B b.subJob C c.subJob D d.subParent A Child B CParent B C Child D
› each node will run the Condor job specified by its accompanying Condor submit file
Job A
Job B Job C
Job D
59http://www.cs.wisc.edu/condor
Submitting a DAG
› To start your DAG, just run condor_submit_dag with your .dag file, and Condor will start a personal DAGMan daemon which to begin running your jobs:
% condor_submit_dag diamond.dag
› condor_submit_dag is run by the schedd DAGMan daemon itself is “watched” by
Condor, so you don’t have to
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DAGMan
Running a DAG
› DAGMan acts as a “meta-scheduler”, managing the submission of your jobs to Condor based on the DAG dependencies.
CondorJobQueue
B C
D
A
A
.dagFile
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DAGMan
Running a DAG (cont’d)
› DAGMan holds & submits jobs to the Condor queue at the appropriate times.
CondorJobQueue D
B
C
B
A
C
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Running a DAG (cont’d)
› In case of a job failure, DAGMan continues until it can no longer make progress, and then creates a “rescue” file with the current state of the DAG.
CondorJobQueue DAGMan
X
D
A
BRescue
File
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Recovering a DAG
› Once the failed job is ready to be re-run, the rescue file can be used to restore the prior state of the DAG.
CondorJobQueue
RescueFile
CDAGMan D
A
B C
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DAGMan
Recovering a DAG (cont’d)
› Once that job completes, DAGMan will continue the DAG as if the failure never happened.
CondorJobQueue
C
D
A
B
D
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DAGMan
Finishing a DAG
› Once the DAG is complete, the DAGMan job itself is finished, and exits.
CondorJobQueue
C
D
A
B
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Additional DAGMan Features
› Provides other handy features for job management…
nodes can have PRE & POST scripts failed nodes can be automatically re-
tried a configurable number of times job submission can be “throttled”
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What about Licensed Jobs?
› e.g. matlab Site license? matlab compiler Octave
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Chirp
› condor_chirp get_file remote local
› condor_chirp put_file local remote
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General User Commands› condor_status View Pool Status
› condor_q View Job Queue› condor_submit Submit new Jobs› condor_rm Remove Jobs› condor_prio Intra-User Prios› condor_history Completed Job Info› condor_submit_dag Submit new DAG› condor_checkpoint Force a checkpoint› condor_compile Link Condor library
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Statistical Bootstrap› Build up from the worker side out
› The matlab/octave worker:
› worker.m:
#!/s/octave/bin/octave -q
load "subset" subset;
subset = subset(floor(rand(10,1) .* 1000));
printf("%f ", mean(subset));
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Submit file
universe = vanilla
executable = worker.m
should_transfer_files = true
when_to_transfer_output = on_exit
transfer_input_files = subset
output = mean.$(PROCESS)
error = foo
log = log
queue 10
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Create the initial datadriver.m
#!/s/octave/bin/octave –qdist_size = 100000;d = rand(dist_size, 1) .* 500;subset = d(floor(rand(1000,1) .*
100000));save "subset" subset;
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Add the submission tothe driver script…
#!/s/octave/bin/octave –q
dist_size = 100000;
d = rand(dist_size, 1) .* 500;
subset = d(floor(rand(1000,1) .* 100000));
save "subset" subset;
system("condor_submit submit");
system("condor_wait log");
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Parallel convergence checking:
Another DAGman example› Evaluating a function at many
points
› Check for convergence -> retry
› Particle Swarm Optimization
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Any Guesses?
› Who has thoughts?
› Best to work from “inside out”
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The submit file# submitRandom
universe = vanilla
executable = random.sh
Should_transfer_files = yes
When_to_transfer_output = on_exit
output = out
log = log
queue
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Next step: the inner DAG
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First Last Node
Node0
Node1 Node2 Node3 Node4
Node11
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The inner DAG file
Job Node0 submitRandom
Job Node1 submitRandom
Job Node2 submitRandom
Job Node3 submitRandom
PARENT Node0 CHILD Node1
PARENT Node0 CHILD Node2
PARENT Node0 CHILD Node3
Job Node11 submitRandom
PARENT Node1, Node2, Node3 CHILD Node11
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How to iterate
› DAGman has simple control structures (Makes it reliable)
› SUBDAGs!
› Remember what happens if post fails?
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The Outer Dag› Another Degenerate Dag
(But Useful!)
88
Post Script (with exit value)
SubDag (with retry)t
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The outer DAG file
####### Outer.dag #############
SUBDAG EXTERNAL A inner.dag
SCRIPT POST A converge.sh
RETRY A 10
#### converge.sh could look like
#!/bin/sh
echo "Checking convergence" >> converge
exit 1
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Let’s run that…
› condor_submit_dag outer.dag
› Does it work? How can you tell?
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DAGman a bit verbose…$ condor_submit_dag outer.dag
-----------------------------------------------------------------------
File for submitting this DAG to Condor : submit.dag.condor.sub
Log of DAGMan debugging messages : submit.dag.dagman.out
Log of Condor library output : submit.dag.lib.out
Log of Condor library error messages : submit.dag.lib.err
Log of the life of condor_dagman itself : submit.dag.dagman.log
-no_submit given, not submitting DAG to Condor. You can do this with:
"condor_submit submit.dag.condor.sub"
-----------------------------------------------------------------------
-----------------------------------------------------------------------
File for submitting this DAG to Condor : outer.dag.condor.sub
Log of DAGMan debugging messages : outer.dag.dagman.out
Log of Condor library output : outer.dag.lib.out
Log of Condor library error messages : outer.dag.lib.err
Log of the life of condor_dagman itself : outer.dag.dagman.log
Submitting job(s).
Logging submit event(s).
1 job(s) submitted to cluster 721.
-----------------------------------------------------------------------
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Debugging helps
› Look in the user log file, “log”
› Look in the DAGman debugging log
› “foo”.dagman.out
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What does converge.sh need
› Note the output files?
› How to make them unique?
› Add DAG variables to inner dag And submitRandom file
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The submit file (again)
# submitRandom
universe = vanilla
executable = random.sh
output = out
log = log
queue
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The submit file
# submitRandom
universe = vanilla
executable = random.sh
output = out.$(NodeNumber)
log = log
queue
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The inner DAG file (again)
Job Node0 submit_pre
Job Node1 submitRandom
Job Node2 submitRandom
Job Node3 submitRandom
PARENT Node0 CHILD Node1
PARENT Node0 CHILD Node2
PARENT Node0 CHILD Node3
Job Node11 submit_post
PARENT Node1 CHILD Node11
PARENT Node2 CHILD Node11
PARENT Node3 CHILD Node11
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The inner DAG file (again)
Job Node0 submit_pre
Job Node1 submitRandom
Job Node2 submitRandom
Job Node3 submitRandom
…
VARS Node1 NodeNumber=“1”
VARS Node2 NodeNumber=“2”
VARS Node3 NodeNumber=“3”
…
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Then converge.sh sees:
$ ls out.*
out.1 out.10 out.2 out.3 out.4 out.5 out.6 out.7 out.8 out.9
$
› And can act accordingly…
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Thank you!
Check us out on the Web:http://www.condorproject.org
Email:[email protected]